---
title: Claude Fable 5.1 and Claude Mythos 5.1 migration guide
url: https://platform.claude.com/docs/en/models/fable-5-1/migration-guide
description: Switch to Claude Fable 5.1 and Claude Mythos 5.1 from Claude Fable 5, Claude Mythos 5, Claude Opus 5, or Claude Opus 4.8 with this migration guide. The guidance to enable Claude Fable 5.1 and Claude Mythos 5.1 includes model IDs, breaking changes, and migration checklists.
---

<Note>
  This guide covers migrating [Messages API](https://platform.claude.com/docs/en/build-with-claude/working-with-messages) code. If you use [Claude Managed Agents](https://platform.claude.com/docs/en/managed-agents/overview), no changes beyond updating the model name are required.
</Note>

Let Claude Code migrate your code for you

```text
/claude-api migrate this project to claude-fable-5-1
```

[Claude Fable 5.1](https://platform.claude.com/docs/en/models/fable-5-1/whats-new-fable-5-1) succeeds Claude Fable 5 at the same input and output prices, with cache reads at a quarter of the cost. It’s available on the Claude API, [Amazon Bedrock](https://platform.claude.com/docs/en/build-with-claude/claude-in-amazon-bedrock), [Claude Platform on AWS](https://platform.claude.com/docs/en/build-with-claude/claude-platform-on-aws), [Claude Models on Google Cloud (Anthropic managed)](https://platform.claude.com/docs/en/build-with-claude/claude-models-on-google-cloud/anthropic-managed), [Claude Models on Google Cloud (Google managed)](https://platform.claude.com/docs/en/build-with-claude/claude-models-on-google-cloud/google-managed), and [Microsoft Foundry](https://platform.claude.com/docs/en/build-with-claude/claude-in-microsoft-foundry). Claude Fable 5.1 doesn’t require access approval. [Claude Mythos 5.1](https://platform.claude.com/docs/en/models/mythos-5-1/overview) shares the same capabilities and is available only to organizations verified through Anthropic’s verification programs, such as the [Cyber Verification Program](https://support.claude.com/en/articles/14604842). To request access, apply to the program that covers your use case or contact your Anthropic account team. For behavioral differences and prompting patterns, see [Prompting Claude Fable 5.1](https://platform.claude.com/docs/en/build-with-claude/prompt-engineering/prompting-claude-fable-5-1).

The baseline settings shared by `claude-fable-5-1` and `claude-mythos-5-1`:

* **Thinking:** [Adaptive thinking](https://platform.claude.com/docs/en/build-with-claude/thinking) is always on, unchanged from Claude Fable 5. The model determines when and how much to think. No `thinking` configuration is required. Both `thinking: {type: "disabled"}` and manual extended thinking (`thinking: {type: "enabled", budget_tokens: N}`) return a 400 error.
* **Prefill:** Prefilling the assistant message returns a 400 error, unchanged from Claude Fable 5. Use system prompt instructions instead.
* **Tool choice:** `{type: "auto"}` (the default) and `{type: "none"}` are supported. Forcing a tool call with `{type: "any"}` or `{type: "tool", name: "..."}` returns a 400 error. See [Breaking changes](https://platform.claude.com/docs/en/models/fable-5-1/migration-guide#fable-5-1-breaking-changes).
* **Preserved thinking across models:** Claude Fable 5.1 and Claude Mythos 5.1 read thinking blocks from Claude Opus 5, Claude Fable 5, Claude Mythos 5, and earlier Claude models. None of those models can read blocks from Claude Fable 5.1 or Claude Mythos 5.1. See [Breaking changes](https://platform.claude.com/docs/en/models/fable-5-1/migration-guide#fable-5-1-breaking-changes).
* **Edits to earlier turns:** A thinking block stays valid only while everything sent before it is unchanged, so keep the conversation history append-only. See [Editing earlier turns invalidates thinking blocks](https://platform.claude.com/docs/en/models/fable-5-1/migration-guide#fable-5-1-preserved-thinking).
* **Context window and output:** Both models have a [1M token context window](https://platform.claude.com/docs/en/build-with-claude/context-windows) and return up to 128k output tokens for each request.
* **Pricing:** $10 USD per million input tokens and $50 USD per million output tokens, the same as Claude Fable 5. Prompt cache reads are $0.25 USD per million tokens, a quarter of the Claude Fable 5 rate. See [Claude pricing](https://platform.claude.com/docs/en/about-claude/pricing).
* **Data retention:** Both models require 30-day data retention, aren’t available under zero data retention (ZDR) arrangements unless expressly authorized by Anthropic, and are designated Covered Models, the same as Claude Fable 5 and Claude Mythos 5. On the Claude API, a request from an organization or workspace without 30-day retention returns a 400 `invalid_request_error`. Organizations with a ZDR arrangement should contact their Anthropic account team or configure retention for individual workspaces. See [Model-specific data retention requirements](https://platform.claude.com/docs/en/manage-claude/api-and-data-retention#model-specific-data-retention-requirements) for per-platform details.
* **Priority Tier:** Neither model is supported on [Priority Tier](https://platform.claude.com/docs/en/api/service-tiers#supported-models). Claude Fable 5 is.

## Migrating to Claude Fable 5.1 from Claude Fable 5

Migration is mostly drop-in. The API surface, limits, per-token pricing, tokenizer, always-on adaptive thinking, refusal handling, and `stop_details` categories all match Claude Fable 5. The following changes apply:

* A request that forces a tool call gets a 400 error.
* Only Claude Fable 5.1 and Claude Mythos 5.1 read Claude Fable 5.1’s thinking blocks.
* [Editing earlier turns](https://platform.claude.com/docs/en/models/fable-5-1/migration-guide#fable-5-1-preserved-thinking) invalidates later thinking blocks.
* Cache reads cost less.
* The advisor tool (beta) accepts fewer advisors.
* Agent-loop behavior differs in three ways.

### Update your model name

```python
model = "claude-fable-5"  # Before
model = "claude-fable-5-1"  # After

# Or, for Claude Mythos 5.1, which offers the same capabilities to verified organizations:
model = "claude-mythos-5-1"  # After
```

### Breaking changes

1. **Forced tool choice is not supported:** Claude Fable 5 accepts `tool_choice` `auto`, `none`, `any`, and `tool`. On `claude-fable-5-1`, `{type: "any"}` and `{type: "tool", name: "..."}` return a 400 `invalid_request_error`:

   ```text wrap
   tool_choice: type "tool" and "any" are not supported for this model.
   ```

   The check applies on the Messages API, the Message Batches API, and the [token counting](https://platform.claude.com/docs/en/build-with-claude/token-counting) endpoint.

   Before (Claude Fable 5):

   <CodeGroup>
     ```bash cURL
     curl -sS https://api.anthropic.com/v1/messages \
       -H "content-type: application/json" \
       -H "x-api-key: $ANTHROPIC_API_KEY" \
       -H "anthropic-version: 2026-10-21" \
       -d '{
         "model": "claude-fable-5",
         "max_tokens": 16000,
         "tools": [
           {
             "name": "record_summary",
             "description": "Record the structured summary of the document.",
             "input_schema": {
               "type": "object",
               "properties": {"summary": {"type": "string"}},
               "required": ["summary"]
             }
           }
         ],
         "tool_choice": {"type": "tool", "name": "record_summary"},
         "messages": [
           {"role": "user", "content": "Summarize: The meeting moved to Thursday."}
         ]
       }'
     ```

     ```bash CLI
     ant messages create <<'YAML'
     model: claude-fable-5
     max_tokens: 16000
     tools:
       - name: record_summary
         description: Record the structured summary of the document.
         input_schema:
           type: object
           properties:
             summary:
               type: string
           required: [summary]
     tool_choice:
       type: tool
       name: record_summary
     messages:
       - role: user
         content: "Summarize: The meeting moved to Thursday."
     YAML
     ```

     ```python Python
     client = anthropic.Anthropic()

     record_summary_tool = {
         "name": "record_summary",
         "description": "Record the structured summary of the document.",
         "input_schema": {
             "type": "object",
             "properties": {"summary": {"type": "string"}},
             "required": ["summary"],
         },
     }

     response = client.messages.create(
         model="claude-fable-5",
         max_tokens=16000,
         tools=[record_summary_tool],
         tool_choice={"type": "tool", "name": "record_summary"},
         messages=[{"role": "user", "content": "Summarize: The meeting moved to Thursday."}],
     )
     print(response.content)
     ```

     ```typescript TypeScript
     const client = new Anthropic();

     const response = await client.messages.create({
       model: "claude-fable-5",
       max_tokens: 16000,
       tools: [
         {
           name: "record_summary",
           description: "Record the structured summary of the document.",
           input_schema: {
             type: "object",
             properties: { summary: { type: "string" } },
             required: ["summary"]
           }
         }
       ],
       tool_choice: { type: "tool", name: "record_summary" },
       messages: [{ role: "user", content: "Summarize: The meeting moved to Thursday." }]
     });

     console.log(response.content);
     ```

     ```csharp C#
     AnthropicClient client = new();

     var parameters = new MessageCreateParams
     {
         Model = Model.ClaudeFable5,
         MaxTokens = 16000,
         Tools = [
             new ToolUnion(new Tool()
             {
                 Name = "record_summary",
                 Description = "Record the structured summary of the document.",
                 InputSchema = new InputSchema()
                 {
                     Properties = new Dictionary<string, JsonElement>
                     {
                         ["summary"] = JsonSerializer.SerializeToElement(new { type = "string" }),
                     },
                     Required = ["summary"],
                 },
             }),
         ],
         ToolChoice = new ToolChoiceTool { Name = "record_summary" },
         Messages = [new UserMessageParam { Content = "Summarize: The meeting moved to Thursday." }]
     };

     var message = await client.Messages.Create(parameters);
     Console.WriteLine(message);
     ```

     ```go Go
     client := anthropic.NewClient()

     response, err := client.Messages.New(context.TODO(), anthropic.MessageNewParams{
     	Model:     anthropic.ModelClaudeFable5,
     	MaxTokens: 16000,
     	Tools: []anthropic.ToolUnionParam{
     		{OfTool: &anthropic.ToolParam{
     			Name:        "record_summary",
     			Description: anthropic.String("Record the structured summary of the document."),
     			InputSchema: anthropic.ToolInputSchemaParam{
     				Properties: map[string]any{
     					"summary": map[string]any{"type": "string"},
     				},
     				Required: []string{"summary"},
     			},
     		}},
     	},
     	ToolChoice: anthropic.ToolChoiceUnionParam{OfTool: &anthropic.ToolChoiceToolParam{Name: "record_summary"}},
     	Messages: []anthropic.MessageParam{
     		anthropic.NewUserMessage(anthropic.NewTextBlock("Summarize: The meeting moved to Thursday.")),
     	},
     })
     if err != nil {
     	log.Fatal(err)
     }
     fmt.Println(response.RawJSON())
     ```

     ```java Java

     void main() {
         AnthropicClient client = AnthropicOkHttpClient.fromEnv();

         MessageCreateParams params = MessageCreateParams.builder()
             .model(Model.CLAUDE_FABLE_5)
             .maxTokens(16000L)
             .addTool(Tool.builder()
                 .name("record_summary")
                 .description("Record the structured summary of the document.")
                 .inputSchema(InputSchema.builder()
                     .properties(JsonValue.from(Map.of("summary", Map.of("type", "string"))))
                     .required(List.of("summary"))
                     .build())
                 .build())
             .toolChoice(ToolChoice.ofTool(ToolChoiceTool.builder()
                 .name("record_summary")
                 .build()))
             .addUserMessage("Summarize: The meeting moved to Thursday.")
             .build();

         Message response = client.messages().create(params);
         IO.println(response);
     }
     ```

     ```php PHP
     $client = new Client();

     $message = $client->messages->create(
         maxTokens: 16000,
         messages: [
             ['role' => 'user', 'content' => 'Summarize: The meeting moved to Thursday.']
         ],
         model: Model::CLAUDE_FABLE_5,
         toolChoice: ['type' => 'tool', 'name' => 'record_summary'],
         tools: [
             [
                 'name' => 'record_summary',
                 'description' => 'Record the structured summary of the document.',
                 'input_schema' => [
                     'type' => 'object',
                     'properties' => [
                         'summary' => ['type' => 'string']
                     ],
                     'required' => ['summary']
                 ]
             ]
         ],
     );

     echo $message;
     ```

     ```ruby Ruby
     client = Anthropic::Client.new

     message = client.messages.create(
       model: Anthropic::Model::CLAUDE_FABLE_5,
       max_tokens: 16000,
       tools: [
         {
           name: "record_summary",
           description: "Record the structured summary of the document.",
           input_schema: {
             type: "object",
             properties: { summary: { type: "string" } },
             required: ["summary"]
           }
         }
       ],
       tool_choice: { type: "tool", name: "record_summary" },
       messages: [
         { role: "user", content: "Summarize: The meeting moved to Thursday." }
       ]
     )
     puts message
     ```
   </CodeGroup>

   After (Claude Fable 5.1): leave `tool_choice` at `auto`, name the tool in the instruction, and set `strict: true` so the call matches your schema. (In a [CMEK](https://platform.claude.com/docs/en/manage-claude/cmek) organization, where [structured outputs](https://platform.claude.com/docs/en/build-with-claude/structured-outputs), including `strict: true`, are not available on Claude Fable models, rely on the instruction alone.) For example:

   <CodeGroup>
     ```bash cURL
     curl -sS https://api.anthropic.com/v1/messages \
       -H "content-type: application/json" \
       -H "x-api-key: $ANTHROPIC_API_KEY" \
       -H "anthropic-version: 2026-10-21" \
       -d '{
         "model": "claude-fable-5-1",
         "max_tokens": 16000,
         "tools": [
           {
             "name": "record_summary",
             "description": "Record the structured summary of the document.",
             "strict": true,
             "input_schema": {
               "type": "object",
               "properties": {"summary": {"type": "string"}},
               "required": ["summary"],
               "additionalProperties": false
             }
           }
         ],
         "tool_choice": {"type": "auto"},
         "messages": [
           {"role": "user", "content": "Summarize: The meeting moved to Thursday. Call the record_summary tool with your result."}
         ]
       }'
     ```

     ```bash CLI
     ant messages create <<'YAML'
     model: claude-fable-5-1
     max_tokens: 16000
     tools:
       - name: record_summary
         description: Record the structured summary of the document.
         strict: true
         input_schema:
           type: object
           properties:
             summary:
               type: string
           required: [summary]
           additionalProperties: false
     tool_choice:
       type: auto
     messages:
       - role: user
         content: "Summarize: The meeting moved to Thursday. Call the record_summary tool with your result."
     YAML
     ```

     ```python Python
     client = anthropic.Anthropic()

     record_summary_tool = {
         "name": "record_summary",
         "description": "Record the structured summary of the document.",
         "strict": True,
         "input_schema": {
             "type": "object",
             "properties": {"summary": {"type": "string"}},
             "required": ["summary"],
             "additionalProperties": False,
         },
     }

     response = client.messages.create(
         model="claude-fable-5-1",
         max_tokens=16000,
         tools=[record_summary_tool],
         tool_choice={"type": "auto"},
         messages=[
             {
                 "role": "user",
                 "content": "Summarize: The meeting moved to Thursday. Call the record_summary tool with your result.",
             }
         ],
     )
     print(response.content)
     ```

     ```typescript TypeScript
     const client = new Anthropic();

     const response = await client.messages.create({
       model: "claude-fable-5-1",
       max_tokens: 16000,
       tools: [
         {
           name: "record_summary",
           description: "Record the structured summary of the document.",
           strict: true,
           input_schema: {
             type: "object",
             properties: { summary: { type: "string" } },
             required: ["summary"],
             additionalProperties: false
           }
         }
       ],
       tool_choice: { type: "auto" },
       messages: [
         {
           role: "user",
           content:
             "Summarize: The meeting moved to Thursday. Call the record_summary tool with your result."
         }
       ]
     });

     console.log(response.content);
     ```

     ```csharp C#
     AnthropicClient client = new();

     var parameters = new MessageCreateParams
     {
         Model = Model.ClaudeFable5_1,
         MaxTokens = 16000,
         Tools = [
             new ToolUnion(new Tool()
             {
                 Name = "record_summary",
                 Description = "Record the structured summary of the document.",
                 Strict = true,
                 InputSchema = new InputSchema(new Dictionary<string, JsonElement>
                 {
                     ["properties"] = JsonSerializer.SerializeToElement(new Dictionary<string, object>
                     {
                         ["summary"] = new { type = "string" },
                     }),
                     ["required"] = JsonSerializer.SerializeToElement(new[] { "summary" }),
                     ["additionalProperties"] = JsonSerializer.SerializeToElement(false),
                 }),
             }),
         ],
         ToolChoice = new ToolChoiceAuto(),
         Messages = [
             new UserMessageParam { Content = "Summarize: The meeting moved to Thursday. Call the record_summary tool with your result." }
         ]
     };

     var message = await client.Messages.Create(parameters);
     Console.WriteLine(message);
     ```

     ```go Go
     client := anthropic.NewClient()

     response, err := client.Messages.New(context.TODO(), anthropic.MessageNewParams{
     	Model:     anthropic.ModelClaudeFable5_1,
     	MaxTokens: 16000,
     	Tools: []anthropic.ToolUnionParam{
     		{OfTool: &anthropic.ToolParam{
     			Name:        "record_summary",
     			Description: anthropic.String("Record the structured summary of the document."),
     			Strict:      anthropic.Bool(true),
     			InputSchema: anthropic.ToolInputSchemaParam{
     				Properties: map[string]any{
     					"summary": map[string]any{"type": "string"},
     				},
     				Required: []string{"summary"},
     				ExtraFields: map[string]any{
     					"additionalProperties": false,
     				},
     			},
     		}},
     	},
     	ToolChoice: anthropic.ToolChoiceUnionParam{OfAuto: &anthropic.ToolChoiceAutoParam{}},
     	Messages: []anthropic.MessageParam{
     		anthropic.NewUserMessage(anthropic.NewTextBlock("Summarize: The meeting moved to Thursday. Call the record_summary tool with your result.")),
     	},
     })
     if err != nil {
     	log.Fatal(err)
     }
     fmt.Println(response.RawJSON())
     ```

     ```java Java

     void main() {
         AnthropicClient client = AnthropicOkHttpClient.fromEnv();

         MessageCreateParams params = MessageCreateParams.builder()
             .model(Model.CLAUDE_FABLE_5_1)
             .maxTokens(16000L)
             .addTool(Tool.builder()
                 .name("record_summary")
                 .description("Record the structured summary of the document.")
                 .inputSchema(InputSchema.builder()
                     .properties(JsonValue.from(Map.of("summary", Map.of("type", "string"))))
                     .putAdditionalProperty("required", JsonValue.from(List.of("summary")))
                     .putAdditionalProperty("additionalProperties", JsonValue.from(false))
                     .build())
                 .strict(true)
                 .build())
             .toolChoice(ToolChoice.ofAuto(ToolChoiceAuto.builder().build()))
             .addUserMessage("Summarize: The meeting moved to Thursday. Call the record_summary tool with your result.")
             .build();

         Message response = client.messages().create(params);
         IO.println(response);
     }
     ```

     ```php PHP
     $client = new Client();

     $message = $client->messages->create(
         maxTokens: 16000,
         messages: [
             ['role' => 'user', 'content' => 'Summarize: The meeting moved to Thursday. Call the record_summary tool with your result.']
         ],
         model: 'claude-fable-5-1',
         toolChoice: ['type' => 'auto'],
         tools: [
             [
                 'name' => 'record_summary',
                 'description' => 'Record the structured summary of the document.',
                 'strict' => true,
                 'input_schema' => [
                     'type' => 'object',
                     'properties' => [
                         'summary' => ['type' => 'string']
                     ],
                     'required' => ['summary'],
                     'additionalProperties' => false
                 ]
             ]
         ],
     );

     echo $message;
     ```

     ```ruby Ruby
     client = Anthropic::Client.new

     message = client.messages.create(
       model: Anthropic::Model::CLAUDE_FABLE_5_1,
       max_tokens: 16000,
       tools: [
         {
           name: "record_summary",
           description: "Record the structured summary of the document.",
           strict: true,
           input_schema: {
             type: "object",
             properties: { summary: { type: "string" } },
             required: ["summary"],
             additionalProperties: false
           }
         }
       ],
       tool_choice: { type: "auto" },
       messages: [
         { role: "user", content: "Summarize: The meeting moved to Thursday. Call the record_summary tool with your result." }
       ]
     )
     puts message
     ```
   </CodeGroup>

   See [Strict tool use](https://platform.claude.com/docs/en/agents-and-tools/tool-use/strict-tool-use) and [Forcing tool use](https://platform.claude.com/docs/en/agents-and-tools/tool-use/define-tools#forcing-tool-use). If you forced a tool only to get schema-conformant JSON, use [JSON outputs](https://platform.claude.com/docs/en/build-with-claude/structured-outputs#usage) (`output_config.format`) instead.

   If your application, rather than the user, requires a specific tool call on the current turn of a multi-turn conversation, append a [mid-conversation system message](https://platform.claude.com/docs/en/build-with-claude/mid-conversation-system-messages) after the latest `user` turn. Name the tool, say the call is required for this turn, and tell Claude to open its response with it. Because the message is appended rather than written into the top-level `system` prompt, earlier turns stay byte-identical and keep their [prompt cache](https://platform.claude.com/docs/en/build-with-claude/prompt-caching) hits:

   <CodeGroup>
     ```bash cURL
     curl -sS https://api.anthropic.com/v1/messages \
       -H "content-type: application/json" \
       -H "x-api-key: $ANTHROPIC_API_KEY" \
       -H "anthropic-version: 2026-10-21" \
       -d '{
         "model": "claude-fable-5-1",
         "max_tokens": 16000,
         "system": "You are a customer support assistant for an online electronics store.",
         "tools": [
           {
             "name": "search_help_center",
             "description": "Search the help center for policy and troubleshooting articles.",
             "strict": true,
             "input_schema": {
               "type": "object",
               "properties": {"query": {"type": "string"}},
               "required": ["query"],
               "additionalProperties": false
             }
           }
         ],
         "messages": [
           {"role": "user", "content": "My headphones from order A1234 arrived yesterday."},
           {"role": "assistant", "content": "Thanks for confirming. How can I help with order A1234?"},
           {"role": "user", "content": "I opened the box. Can I still return them?"},
           {
             "role": "system",
             "content": "Tool-use requirement for the current turn: the application requires a call to the search_help_center tool in your response to the latest message from the user. Begin your response with the search_help_center tool call. Do not reply with text only."
           }
         ]
       }'
     ```

     ```bash CLI
     ant messages create <<'YAML'
     model: claude-fable-5-1
     max_tokens: 16000
     system: You are a customer support assistant for an online electronics store.
     tools:
       - name: search_help_center
         description: Search the help center for policy and troubleshooting articles.
         strict: true
         input_schema:
           type: object
           properties:
             query:
               type: string
           required: [query]
           additionalProperties: false
     messages:
       - role: user
         content: My headphones from order A1234 arrived yesterday.
       - role: assistant
         content: Thanks for confirming. How can I help with order A1234?
       - role: user
         content: I opened the box. Can I still return them?
       - role: system
         content: >-
           Tool-use requirement for the current turn: the application requires a call
           to the search_help_center tool in your response to the user's latest message.
           Begin your response with the search_help_center tool call. Do not reply with
           text only.
     YAML
     ```

     ```python Python
     client = anthropic.Anthropic()

     search_help_center_tool = {
         "name": "search_help_center",
         "description": "Search the help center for policy and troubleshooting articles.",
         "strict": True,
         "input_schema": {
             "type": "object",
             "properties": {"query": {"type": "string"}},
             "required": ["query"],
             "additionalProperties": False,
         },
     }

     response = client.messages.create(
         model="claude-fable-5-1",
         max_tokens=16000,
         system="You are a customer support assistant for an online electronics store.",
         tools=[search_help_center_tool],
         messages=[
             {
                 "role": "user",
                 "content": "My headphones from order A1234 arrived yesterday.",
             },
             {
                 "role": "assistant",
                 "content": "Thanks for confirming. How can I help with order A1234?",
             },
             {"role": "user", "content": "I opened the box. Can I still return them?"},
             # The application requires a help center lookup before any policy
             # answer. Appending the requirement as a system message leaves the
             # earlier turns unchanged.
             {
                 "role": "system",
                 "content": "Tool-use requirement for the current turn: the application requires a call to the search_help_center tool in your response to the user's latest message. Begin your response with the search_help_center tool call. Do not reply with text only.",
             },
         ],
     )
     print(response.content)
     ```

     ```typescript TypeScript
     const client = new Anthropic();

     const response = await client.messages.create({
       model: "claude-fable-5-1",
       max_tokens: 16000,
       system: "You are a customer support assistant for an online electronics store.",
       tools: [
         {
           name: "search_help_center",
           description: "Search the help center for policy and troubleshooting articles.",
           strict: true,
           input_schema: {
             type: "object",
             properties: { query: { type: "string" } },
             required: ["query"],
             additionalProperties: false
           }
         }
       ],
       messages: [
         { role: "user", content: "My headphones from order A1234 arrived yesterday." },
         { role: "assistant", content: "Thanks for confirming. How can I help with order A1234?" },
         { role: "user", content: "I opened the box. Can I still return them?" },
         // The application requires a help center lookup before any policy
         // answer. Appending the requirement as a system message leaves the
         // earlier turns unchanged.
         {
           role: "system",
           content:
             "Tool-use requirement for the current turn: the application requires a call to the search_help_center tool in your response to the user's latest message. Begin your response with the search_help_center tool call. Do not reply with text only."
         }
       ]
     });

     console.log(response.content);
     ```

     ```csharp C#
     AnthropicClient client = new();

     var parameters = new MessageCreateParams
     {
         Model = Model.ClaudeFable5_1,
         MaxTokens = 16000,
         System = "You are a customer support assistant for an online electronics store.",
         Tools = [
             new ToolUnion(new Tool()
             {
                 Name = "search_help_center",
                 Description = "Search the help center for policy and troubleshooting articles.",
                 Strict = true,
                 InputSchema = new InputSchema(new Dictionary<string, JsonElement>
                 {
                     ["properties"] = JsonSerializer.SerializeToElement(new Dictionary<string, object>
                     {
                         ["query"] = new { type = "string" },
                     }),
                     ["required"] = JsonSerializer.SerializeToElement(new[] { "query" }),
                     ["additionalProperties"] = JsonSerializer.SerializeToElement(false),
                 }),
             }),
         ],
         Messages = [
             new UserMessageParam { Content = "My headphones from order A1234 arrived yesterday." },
             new AssistantMessageParam { Content = "Thanks for confirming. How can I help with order A1234?" },
             new UserMessageParam { Content = "I opened the box. Can I still return them?" },
             // The application requires a help center lookup before any policy
             // answer. Appending the requirement as a system message leaves the
             // earlier turns unchanged.
             new SystemMessageParam
             {
                 Content = "Tool-use requirement for the current turn: the application requires a call to the search_help_center tool in your response to the user's latest message. Begin your response with the search_help_center tool call. Do not reply with text only."
             }
         ]
     };

     var message = await client.Messages.Create(parameters);
     Console.WriteLine(message);
     ```

     ```go Go
     client := anthropic.NewClient()

     response, err := client.Messages.New(context.TODO(), anthropic.MessageNewParams{
     	Model:     anthropic.ModelClaudeFable5_1,
     	MaxTokens: 16000,
     	System: []anthropic.TextBlockParam{
     		{Text: "You are a customer support assistant for an online electronics store."},
     	},
     	Tools: []anthropic.ToolUnionParam{
     		{OfTool: &anthropic.ToolParam{
     			Name:        "search_help_center",
     			Description: anthropic.String("Search the help center for policy and troubleshooting articles."),
     			Strict:      anthropic.Bool(true),
     			InputSchema: anthropic.ToolInputSchemaParam{
     				Properties: map[string]any{
     					"query": map[string]any{"type": "string"},
     				},
     				Required: []string{"query"},
     				ExtraFields: map[string]any{
     					"additionalProperties": false,
     				},
     			},
     		}},
     	},
     	Messages: []anthropic.MessageParam{
     		anthropic.NewUserMessage(anthropic.NewTextBlock("My headphones from order A1234 arrived yesterday.")),
     		anthropic.NewAssistantMessage(anthropic.NewTextBlock("Thanks for confirming. How can I help with order A1234?")),
     		anthropic.NewUserMessage(anthropic.NewTextBlock("I opened the box. Can I still return them?")),
     		// The application requires a help center lookup before any policy
     		// answer. Appending the requirement as a system message leaves the
     		// earlier turns unchanged.
     		{OfSystem: &anthropic.SystemMessageParam{
     			Content: []anthropic.TextBlockParam{
     				{Text: "Tool-use requirement for the current turn: the application requires a call to the search_help_center tool in your response to the user's latest message. Begin your response with the search_help_center tool call. Do not reply with text only."},
     			},
     		}},
     	},
     })
     if err != nil {
     	log.Fatal(err)
     }
     fmt.Println(response.RawJSON())
     ```

     ```java Java

     void main() {
         AnthropicClient client = AnthropicOkHttpClient.fromEnv();

         MessageCreateParams params = MessageCreateParams.builder()
             .model(Model.CLAUDE_FABLE_5_1)
             .maxTokens(16000L)
             .system("You are a customer support assistant for an online electronics store.")
             .addTool(Tool.builder()
                 .name("search_help_center")
                 .description("Search the help center for policy and troubleshooting articles.")
                 .inputSchema(InputSchema.builder()
                     .properties(JsonValue.from(Map.of("query", Map.of("type", "string"))))
                     .putAdditionalProperty("required", JsonValue.from(List.of("query")))
                     .putAdditionalProperty("additionalProperties", JsonValue.from(false))
                     .build())
                 .strict(true)
                 .build())
             .addUserMessage("My headphones from order A1234 arrived yesterday.")
             .addAssistantMessage("Thanks for confirming. How can I help with order A1234?")
             .addUserMessage("I opened the box. Can I still return them?")
             // The application requires a help center lookup before any policy
             // answer. Appending the requirement as a system message leaves the
             // earlier turns unchanged.
             .addSystemMessage("Tool-use requirement for the current turn: the application requires a call to the search_help_center tool in your response to the user's latest message. Begin your response with the search_help_center tool call. Do not reply with text only.")
             .build();

         Message response = client.messages().create(params);
         IO.println(response);
     }
     ```

     ```php PHP
     $client = new Client();

     $message = $client->messages->create(
         maxTokens: 16000,
         messages: [
             ['role' => 'user', 'content' => 'My headphones from order A1234 arrived yesterday.'],
             ['role' => 'assistant', 'content' => 'Thanks for confirming. How can I help with order A1234?'],
             ['role' => 'user', 'content' => 'I opened the box. Can I still return them?'],
             // The application requires a help center lookup before any policy
             // answer. Appending the requirement as a system message leaves the
             // earlier turns unchanged.
             ['role' => 'system', 'content' => 'Tool-use requirement for the current turn: the application requires a call to the search_help_center tool in your response to the user\'s latest message. Begin your response with the search_help_center tool call. Do not reply with text only.']
         ],
         model: 'claude-fable-5-1',
         system: 'You are a customer support assistant for an online electronics store.',
         tools: [
             [
                 'name' => 'search_help_center',
                 'description' => 'Search the help center for policy and troubleshooting articles.',
                 'strict' => true,
                 'input_schema' => [
                     'type' => 'object',
                     'properties' => [
                         'query' => ['type' => 'string']
                     ],
                     'required' => ['query'],
                     'additionalProperties' => false
                 ]
             ]
         ],
     );

     echo $message;
     ```

     ```ruby Ruby
     client = Anthropic::Client.new

     message = client.messages.create(
       model: Anthropic::Model::CLAUDE_FABLE_5_1,
       max_tokens: 16000,
       system: "You are a customer support assistant for an online electronics store.",
       tools: [
         {
           name: "search_help_center",
           description: "Search the help center for policy and troubleshooting articles.",
           strict: true,
           input_schema: {
             type: "object",
             properties: { query: { type: "string" } },
             required: ["query"],
             additionalProperties: false
           }
         }
       ],
       messages: [
         { role: "user", content: "My headphones from order A1234 arrived yesterday." },
         { role: "assistant", content: "Thanks for confirming. How can I help with order A1234?" },
         { role: "user", content: "I opened the box. Can I still return them?" },
         # The application requires a help center lookup before any policy
         # answer. Appending the requirement as a system message leaves the
         # earlier turns unchanged.
         {
           role: "system",
           content: "Tool-use requirement for the current turn: the application requires a call to the search_help_center tool in your response to the user's latest message. Begin your response with the search_help_center tool call. Do not reply with text only."
         }
       ]
     )
     puts message
     ```
   </CodeGroup>

   Keep the `role: "system"` message in the history on later requests, as with any other turn. Mid-conversation system messages need no beta header. `tool_choice: {"type": "none"}` still works for a turn that must not call tools.

2. **Only Claude Fable 5.1 and Claude Mythos 5.1 read Claude Fable 5.1’s thinking blocks:** Every `thinking` block records which model produced it. Claude Fable 5.1 reads its own blocks and those from Claude Mythos 5.1, Claude Opus 5, Claude Fable 5, Claude Mythos 5, and earlier Claude models. A conversation moving onto `claude-fable-5-1` from any of those keeps its earlier reasoning. The condition is one-way: apart from Claude Mythos 5.1, none of those models can read Claude Fable 5.1’s blocks.

   A conversation that ran on Claude Fable 5.1 can land on another model, older or newer, through a router switch, a client-side retry, or a [classifier refusal fallback](https://platform.claude.com/docs/en/build-with-claude/refusals-and-fallback), including a [server-side fallback](https://platform.claude.com/docs/en/build-with-claude/refusals-and-fallback#server-side-fallback). The API removes the blocks that model can’t read before it receives them, the request succeeds, and you aren’t billed for the dropped input tokens. The target model re-plans without that reasoning, which can raise cost and latency on the first turn after the switch. To see what was dropped, send the `thinking-binding-controls-2026-08-01` [beta header](https://platform.claude.com/docs/en/api/beta-headers): responses then carry an `input_transformations` array naming each dropped block with `reason: "model_binding_mismatch"`. See [Switching models mid-conversation](https://platform.claude.com/docs/en/build-with-claude/preserved-thinking#switching-models).

3. **Editing earlier turns invalidates thinking blocks:** On Claude Fable 5.1 and Claude Mythos 5.1, a thinking block you send back stays valid only while everything sent before it is unchanged: the `system` prompt, the `tools`, and the earlier messages. Claude Code, claude.ai, [Claude Managed Agents](https://platform.claude.com/docs/en/managed-agents/overview), and the [Claude Agent SDK](https://code.claude.com/docs/en/agent-sdk/overview) keep that history intact for you. If your code builds the `messages` array itself, this item applies to you, and [Preserved thinking](https://platform.claude.com/docs/en/build-with-claude/preserved-thinking) is the full integration guide.

   The `thinking.block_binding.prefix_mismatch_behavior` field (beta header `thinking-binding-controls-2026-08-01`) sets what the API does with an invalid block. `"error"` rejects the request with a 400 error. `"drop_block"` drops the invalid block and every thinking block after it, and the request succeeds. When a request leaves the field unset, the outcome depends on the model and on when your account was created:

   | Model             | Account created on or after August 31, 2026 | Account created before August 31, 2026    |
   | ----------------- | ------------------------------------------- | ----------------------------------------- |
   | Claude Fable 5.1  | 400 error                                   | No error (failing blocks reach the model) |
   | Claude Mythos 5.1 | 400 error                                   | 400 error                                 |

   To see the 400 error from your own account, set the field to `"error"` on your test requests. Do this before you ship a tool that people run with their own API keys: their accounts can get the 400 error where yours doesn’t. The full table, with the platforms it applies to, is in [When `prefix_mismatch_behavior` is unset](https://platform.claude.com/docs/en/build-with-claude/preserved-thinking#enforcement).

   The 400 error looks like this:

   ```text wrap
   messages.5.content.0: Invalid `signature` in `thinking` block. The block is bound to a different conversation. Remove the block, or set `thinking.block_binding.prefix_mismatch_behavior` to "drop_block". That setting requires the `thinking-binding-controls-2026-08-01` value in the `anthropic-beta` header.
   ```

   The error comes back every time a request sends the invalid block, so a retry loop won’t clear it. To continue without the invalidated reasoning, strip the block the error names and every later `thinking` and `redacted_thinking` block, then retry once. Alternatively, send the `thinking-binding-controls-2026-08-01` [beta header](https://platform.claude.com/docs/en/api/beta-headers) and set `prefix_mismatch_behavior` to `"drop_block"` on every later request in the conversation. The response then reports each dropped block in its `input_transformations` array with `reason: "prefix_binding_mismatch"`:

   <CodeGroup>
     ```bash cURL
     curl https://api.anthropic.com/v1/messages \
       -H "x-api-key: $ANTHROPIC_API_KEY" \
       -H "anthropic-version: 2026-10-21" \
       -H "anthropic-beta: thinking-binding-controls-2026-08-01" \
       -H "content-type: application/json" \
       -d '{
         "model": "claude-fable-5-1",
         "max_tokens": 16000,
         "thinking": {
           "type": "adaptive",
           "block_binding": {
             "prefix_mismatch_behavior": "drop_block"
           }
         },
         "messages": [
           {
             "role": "user",
             "content": "What is the greatest common divisor of 1071 and 462?"
           }
         ]
       }'
     ```

     ```bash CLI
     ant beta:messages create --beta thinking-binding-controls-2026-08-01 <<'YAML'
     model: claude-fable-5-1
     max_tokens: 16000
     thinking:
       type: adaptive
       block_binding:
         prefix_mismatch_behavior: drop_block
     messages:
       - role: user
         content: What is the greatest common divisor of 1071 and 462?
     YAML
     ```

     ```python Python
     client = anthropic.Anthropic()

     response = client.beta.messages.create(
         model="claude-fable-5-1",
         max_tokens=16000,
         thinking={
             "type": "adaptive",
             "block_binding": {"prefix_mismatch_behavior": "drop_block"},
         },
         messages=[
             {
                 "role": "user",
                 "content": "What is the greatest common divisor of 1071 and 462?",
             }
         ],
         betas=["thinking-binding-controls-2026-08-01"],
     )

     for block in response.content:
         if block.type == "text":
             print(block.text)

     print(f"Input transformations: {len(response.input_transformations or [])}")
     ```

     ```typescript TypeScript
     const client = new Anthropic();

     const response = await client.beta.messages.create({
       model: "claude-fable-5-1",
       max_tokens: 16000,
       thinking: {
         type: "adaptive",
         block_binding: { prefix_mismatch_behavior: "drop_block" }
       },
       messages: [
         { role: "user", content: "What is the greatest common divisor of 1071 and 462?" }
       ],
       betas: ["thinking-binding-controls-2026-08-01"]
     });

     for (const block of response.content) {
       if (block.type === "text") {
         console.log(block.text);
       }
     }
     console.log(`Input transformations: ${response.input_transformations?.length ?? 0}`);
     ```

     ```csharp C#
     using Anthropic.Models.Beta;
     using Anthropic.Models.Beta.Messages;
     using Model = Anthropic.Models.Messages.Model;

     AnthropicClient client = new();

     var response = await client.Beta.Messages.Create(
         new()
         {
             Model = Model.ClaudeFable5_1,
             MaxTokens = 16000,
             Thinking = new BetaThinkingConfigAdaptive
             {
                 BlockBinding = new()
                 {
                     PrefixMismatchBehavior = BetaThinkingPrefixMismatchBehavior.DropBlock,
                 },
             },
             Messages =
             [
                 new BetaUserMessageParam
                 {
                     Content = "What is the greatest common divisor of 1071 and 462?",
                 },
             ],
             Betas = [AnthropicBeta.ThinkingBindingControls2026_08_01],
         }
     );

     foreach (var block in response.Content)
     {
         if (block.TryPickText(out var textBlock))
         {
             Console.WriteLine(textBlock.Text);
         }
     }

     Console.WriteLine($"Input transformations: {response.InputTransformations?.Count ?? 0}");
     ```

     ```go Go
     client := anthropic.NewClient()

     response, err := client.Beta.Messages.New(context.TODO(), anthropic.BetaMessageNewParams{
     	Model:     anthropic.ModelClaudeFable5_1,
     	MaxTokens: 16000,
     	Thinking: anthropic.BetaThinkingConfigParamUnion{
     		OfAdaptive: &anthropic.BetaThinkingConfigAdaptiveParam{
     			BlockBinding: anthropic.BetaThinkingBlockBindingParam{
     				PrefixMismatchBehavior: anthropic.BetaThinkingPrefixMismatchBehaviorDropBlock,
     			},
     		},
     	},
     	Messages: []anthropic.BetaMessageParam{
     		anthropic.NewBetaUserMessage(anthropic.NewBetaTextBlock("What is the greatest common divisor of 1071 and 462?")),
     	},
     	Betas: []anthropic.AnthropicBeta{anthropic.AnthropicBetaThinkingBindingControls2026_08_01},
     })
     if err != nil {
     	log.Fatal(err)
     }

     for _, block := range response.Content {
     	if textBlock, ok := block.AsAny().(anthropic.BetaTextBlock); ok {
     		fmt.Println(textBlock.Text)
     	}
     }
     fmt.Printf("Input transformations: %d\n", len(response.InputTransformations))
     ```

     ```java Java
     import com.anthropic.models.beta.AnthropicBeta;
     import com.anthropic.models.beta.messages.BetaMessage;
     import com.anthropic.models.beta.messages.BetaThinkingBlockBinding;
     import com.anthropic.models.beta.messages.BetaThinkingConfigAdaptive;
     import com.anthropic.models.beta.messages.BetaThinkingPrefixMismatchBehavior;
     import com.anthropic.models.beta.messages.MessageCreateParams;
     import com.anthropic.models.messages.Model;

     void main() {
         AnthropicClient client = AnthropicOkHttpClient.fromEnv();

         MessageCreateParams params = MessageCreateParams.builder()
             .model(Model.CLAUDE_FABLE_5_1)
             .maxTokens(16000L)
             .addBeta(AnthropicBeta.THINKING_BINDING_CONTROLS_2026_08_01)
             .thinking(BetaThinkingConfigAdaptive.builder()
                 .blockBinding(BetaThinkingBlockBinding.builder()
                     .prefixMismatchBehavior(BetaThinkingPrefixMismatchBehavior.DROP_BLOCK)
                     .build())
                 .build())
             .addUserMessage("What is the greatest common divisor of 1071 and 462?")
             .build();

         BetaMessage response = client.beta().messages().create(params);

         response.content().stream()
             .flatMap(block -> block.text().stream())
             .forEach(textBlock -> IO.println(textBlock.text()));
         IO.println("Input transformations: "
             + response.inputTransformations().map(List::size).orElse(0));
     }
     ```

     ```php PHP
     use Anthropic\Beta\AnthropicBeta;
     use Anthropic\Beta\Messages\BetaThinkingBlockBinding;
     use Anthropic\Beta\Messages\BetaThinkingConfigAdaptive;
     use Anthropic\Beta\Messages\BetaThinkingPrefixMismatchBehavior;
     use Anthropic\Client;

     $client = new Client();

     $response = $client->beta->messages->create(
         model: 'claude-fable-5-1',
         maxTokens: 16000,
         thinking: BetaThinkingConfigAdaptive::with(
             blockBinding: BetaThinkingBlockBinding::with(
                 prefixMismatchBehavior: BetaThinkingPrefixMismatchBehavior::DROP_BLOCK,
             ),
         ),
         messages: [
             ['role' => 'user', 'content' => 'What is the greatest common divisor of 1071 and 462?'],
         ],
         betas: [AnthropicBeta::THINKING_BINDING_CONTROLS_2026_08_01],
     );

     foreach ($response->content as $block) {
         if ($block->type === 'text') {
             echo $block->text, PHP_EOL;
         }
     }

     echo 'Input transformations: ', count($response->inputTransformations ?? []), PHP_EOL;
     ```

     ```ruby Ruby
     client = Anthropic::Client.new

     response = client.beta.messages.create(
       model: Anthropic::Model::CLAUDE_FABLE_5_1,
       max_tokens: 16_000,
       thinking: {
         type: "adaptive",
         block_binding: {prefix_mismatch_behavior: "drop_block"}
       },
       messages: [
         {role: "user", content: "What is the greatest common divisor of 1071 and 462?"}
       ],
       betas: [Anthropic::AnthropicBeta::THINKING_BINDING_CONTROLS_2026_08_01]
     )

     response.content.each do |block|
       puts block.text if block.type == :text
     end

     puts "Input transformations: #{response.input_transformations&.length || 0}"
     ```
   </CodeGroup>

   The [token counting](https://platform.claude.com/docs/en/build-with-claude/token-counting) endpoint runs the same check. See [Set the mismatch behavior and read `input_transformations`](https://platform.claude.com/docs/en/build-with-claude/preserved-thinking#preserved-thinking-controls) for the response shape and streaming placement.

   Patterns that invalidate later thinking blocks, and what to do instead:

   * Editing, reordering, or removing earlier turns. This includes deleting old tool results, snipping turns out of the middle of the transcript, and client-side compaction that keeps recent turns and their thinking blocks verbatim behind a summary (including background compaction that swaps its summary in a few turns later). Instead, use server-side [compaction](https://platform.claude.com/docs/en/build-with-claude/compaction) or [context editing](https://platform.claude.com/docs/en/build-with-claude/context-editing) ([tool result clearing](https://platform.claude.com/docs/en/build-with-claude/context-editing#tool-result-clearing) for old tool results), or one of the client-side compaction shapes under [Trim context on the server, or compact in a shape that carries no stale thinking](https://platform.claude.com/docs/en/models/fable-5-1/migration-guide#fable-5-1-trim-context).
   * Injecting content you don’t persist, for example a per-turn reminder appended after the `tool_result` blocks and removed on the next request. Instead, send the reminder as a [turn-scoped system message](https://platform.claude.com/docs/en/build-with-claude/mid-conversation-system-messages#turn-scoped-system-messages) and leave it in the history.
   * Rebuilding the top-level `system` prompt or the `tools` array between requests in the same conversation, for example to update the current date or to add or remove a tool. Instead, append a [mid-conversation system message](https://platform.claude.com/docs/en/build-with-claude/mid-conversation-system-messages) that carries the new instruction (“The current date is 2026-09-14.”) or `tool_addition` and `tool_removal` blocks. A tool that wasn’t declared in `tools` at the start can be [defined inside the `tool_addition` block](https://platform.claude.com/docs/en/build-with-claude/mid-conversation-system-messages#define-tools-in-a-message-beta) (beta header `inline-tools-2026-09-15`).
   * An image or document URL that serves different bytes on a later request. The prefix check covers the bytes, not the URL string, so a rotating signed URL for the same file is fine. For content you reference across turns, upload it once with the [Files API](https://platform.claude.com/docs/en/build-with-claude/files) and send the `file_id`, or send base64.

   Each replacement also keeps earlier turns byte-identical and preserves the [prompt cache](https://platform.claude.com/docs/en/build-with-claude/prompt-caching) hits that editing the history, `system` prompt, or `tools` array would lose.

   Patterns that keep working:

   * Append-only histories: adding turns and passing earlier turns back exactly as sent and received, including appended `role: "system"` messages.
   * Removing the oldest thinking blocks (from the start of the history), the newest (from the end), or all of them.
   * Changing `effort`, `max_tokens`, or any other request parameter outside `model`, `system`, `tools`, and `messages`, and adding or moving `cache_control` markers.
   * Server-side compaction and context editing, including [thinking block clearing](https://platform.claude.com/docs/en/build-with-claude/context-editing#thinking-block-clearing). They don’t count as edits, because the check compares the conversation as you sent it.

   To check an existing integration:

   1. Capture the exact request bodies it sends over a few normal turns, including a compaction or a tool change if your product has them. For each pair of consecutive requests, compare the `system` prompt, the `tools` array, and the shared prefix of `messages`. They should be byte-identical up to the newly appended turns. An expected exception is a request that swaps in a signed `compaction` block from [on-demand compaction](https://platform.claude.com/docs/en/build-with-claude/compaction-on-demand): the block replaces the messages it summarizes at the front of `messages`, and everything after it should still match.
   2. Run a normal multi-turn session against `claude-fable-5-1` with the `thinking-binding-controls-2026-08-01` beta header and `prefix_mismatch_behavior: "drop_block"`. Log `input_transformations` on every response. In a session whose responses include thinking blocks, an empty array on every turn means the history is intact. An entry with `reason: "prefix_binding_mismatch"` means something before the block at `path` changed since that block was produced. An entry with `reason: "model_binding_mismatch"` means the conversation switched models, which isn’t a bug in your code. Because every request sets the field, this test works from any account. In CI, set `"error"` instead so an edit fails the run.
   3. Choose a production setting and send it on every request. Use `"error"` if a prefix mismatch can only mean a bug in your code. Use `"drop_block"` if you’d rather drop the affected blocks than fail. Either way, monitor the 400 errors or the `input_transformations` entries.

   Dropping thinking blocks once, at a compaction boundary for example, has little effect. An integration that invalidates prior thinking on every request restarts the prompt cache each time, which can raise cost per task (see [Keep the conversation history append-only](https://platform.claude.com/docs/en/build-with-claude/prompt-engineering/prompting-claude-fable-5-1#keep-the-conversation-history-append-only)).

4. **The advisor tool accepts fewer advisors:** With the [advisor tool](https://platform.claude.com/docs/en/agents-and-tools/tool-use/advisor-tool) (beta), the advisor must be at least as capable as the executor. With a `claude-fable-5-1` executor, a less capable advisor, such as `claude-fable-5` or `claude-opus-5-5`, returns a 400 `invalid_request_error`. Choose an advisor that [Model compatibility](https://platform.claude.com/docs/en/agents-and-tools/tool-use/advisor-tool#model-compatibility) lists for the executor.

### Behavior changes

1. **Fewer parallel tool calls in long agent loops:** In long-running loops where the next independent reads are only implied by the task (custom coding agents, bash-and-editor harnesses, computer use), Claude Fable 5.1 might issue one tool call in each turn. Each extra turn costs tokens, a round trip, and wall-clock time. Append a one-sentence batching instruction after each user message as a [turn-scoped system message](https://platform.claude.com/docs/en/build-with-claude/mid-conversation-system-messages#turn-scoped-system-messages) (`clear_at: "next_user_message"`, beta), or, without the beta, in a text block after the `tool_result` blocks, and leave the earlier copies in the history on later requests. See [Batch independent tool calls in agent loops](https://platform.claude.com/docs/en/build-with-claude/prompt-engineering/prompting-claude-fable-5-1#batch-independent-tool-calls-in-agent-loops).

2. **Fewer progress messages between tool calls:** Claude Fable 5.1 writes fewer status updates during long tool sequences than Claude Fable 5, and its agentic coding summaries are shorter. If your interface renders those updates, set `thinking.display` to `"updates"` (beta) or `"summarized"` and prompt for them explicitly. See [Progress updates between tool calls](https://platform.claude.com/docs/en/build-with-claude/thinking#progress-updates) and [Ask for user-facing progress updates](https://platform.claude.com/docs/en/build-with-claude/prompt-engineering/prompting-claude-fable-5-1#ask-for-user-facing-progress-updates).

3. **Fewer search and retrieval calls at low effort:** At `low` effort Claude Fable 5.1 answers from memory more often than Claude Fable 5 instead of calling a search or retrieval tool. If your product relies on retrieval at low effort, raise effort for those requests or tell the model when to search. See [Search triggering at low effort](https://platform.claude.com/docs/en/build-with-claude/prompt-engineering/prompting-claude-fable-5-1#search-triggering-at-low-effort).

For the differences in prose density, chat formatting, quoting in summaries, and file edits, which don’t affect API integration, see [Changed from Claude Fable 5](https://platform.claude.com/docs/en/models/fable-5-1/whats-new-fable-5-1#changed-from-claude-fable-5).

### Recommended changes

These changes aren’t required, but each one lowers cost or latency or removes a failure mode:

1. **Change effort mid-conversation (beta):** On Claude Fable 5, `output_config.effort` is request-level, and changing it between requests drops cached prefixes from earlier turns. On `claude-fable-5-1`, a `role: "system"` message carrying only `output_config` raises effort for a hard step or lowers it for routine ones without invalidating the [prompt cache](https://platform.claude.com/docs/en/build-with-claude/prompt-caching):

   <CodeGroup>
     ```bash cURL
     # Effort-only system message: the new level takes effect from the next user turn.
     curl https://api.anthropic.com/v1/messages \
       -H "x-api-key: $ANTHROPIC_API_KEY" \
       -H "anthropic-version: 2026-10-21" \
       -H "anthropic-beta: mid-conversation-output-config-2026-07-01" \
       -H "content-type: application/json" \
       -d '{
         "model": "claude-fable-5-1",
         "max_tokens": 4096,
         "output_config": {"effort": "high"},
         "messages": [
           {"role": "user", "content": "Plan a migration from SQLite to PostgreSQL in three short steps."},
           {"role": "assistant", "content": "1. Export the SQLite data. 2. Create the PostgreSQL schema. 3. Import the data and verify row counts."},
           {"role": "system", "content": [], "output_config": {"effort": "low"}},
           {"role": "user", "content": "Summarize the plan in one sentence."}
         ]
       }'
     ```

     ```bash CLI
     ant beta:messages create \
       --beta mid-conversation-output-config-2026-07-01 <<'YAML'
     model: claude-fable-5-1
     max_tokens: 4096
     output_config:
       effort: high
     messages:
       - role: user
         content: Plan a migration from SQLite to PostgreSQL in three short steps.
       - role: assistant
         content: "1. Export the SQLite data. 2. Create the PostgreSQL schema. 3. Import the data and verify row counts."
       # Effort-only system message: the new level takes effect from the next user turn.
       - role: system
         content: []
         output_config:
           effort: low
       - role: user
         content: Summarize the plan in one sentence.
     YAML
     ```

     ```python Python
     client = anthropic.Anthropic()

     response = client.beta.messages.create(
         model="claude-fable-5-1",
         max_tokens=4096,
         output_config={"effort": "high"},
         messages=[
             {
                 "role": "user",
                 "content": "Plan a migration from SQLite to PostgreSQL in three short steps.",
             },
             {
                 "role": "assistant",
                 "content": "1. Export the SQLite data. 2. Create the PostgreSQL schema. 3. Import the data and verify row counts.",
             },
             # Effort-only system message: the new level takes effect from the next user turn.
             {"role": "system", "content": [], "output_config": {"effort": "low"}},
             {"role": "user", "content": "Summarize the plan in one sentence."},
         ],
         betas=["mid-conversation-output-config-2026-07-01"],
     )

     for block in response.content:
         if block.type == "text":
             print(block.text)
     ```

     ```typescript TypeScript
     const client = new Anthropic();

     const response = await client.beta.messages.create({
       model: "claude-fable-5-1",
       max_tokens: 4096,
       output_config: { effort: "high" },
       messages: [
         {
           role: "user",
           content: "Plan a migration from SQLite to PostgreSQL in three short steps."
         },
         {
           role: "assistant",
           content:
             "1. Export the SQLite data. 2. Create the PostgreSQL schema. 3. Import the data and verify row counts."
         },
         // Effort-only system message: the new level takes effect from the next user turn.
         { role: "system", content: [], output_config: { effort: "low" } },
         { role: "user", content: "Summarize the plan in one sentence." }
       ],
       betas: ["mid-conversation-output-config-2026-07-01"]
     });

     for (const block of response.content) {
       if (block.type === "text") {
         console.log(block.text);
       }
     }
     ```

     ```csharp C#
     using Anthropic.Models.Beta;
     using Anthropic.Models.Beta.Messages;
     using Model = Anthropic.Models.Messages.Model;

     AnthropicClient client = new();

     var response = await client.Beta.Messages.Create(new MessageCreateParams
     {
         Model = Model.ClaudeFable5_1,
         MaxTokens = 4096,
         OutputConfig = new() { Effort = Effort.High },
         Messages =
         [
             new BetaUserMessageParam { Content = "Plan a migration from SQLite to PostgreSQL in three short steps." },
             new BetaAssistantMessageParam { Content = "1. Export the SQLite data. 2. Create the PostgreSQL schema. 3. Import the data and verify row counts." },
             // Effort-only system message: the new level takes effect from the next user turn.
             new BetaSystemMessageParam
             {
                 Content = new([]),
                 OutputConfig = new() { Effort = BetaSystemMessageOutputConfigEffort.Low },
             },
             new BetaUserMessageParam { Content = "Summarize the plan in one sentence." },
         ],
         Betas = [AnthropicBeta.MidConversationOutputConfig2026_07_01],
     });

     foreach (var block in response.Content)
     {
         if (block.TryPickText(out var textBlock))
         {
             Console.WriteLine(textBlock.Text);
         }
     }
     ```

     ```go Go
     client := anthropic.NewClient()

     response, err := client.Beta.Messages.New(context.Background(), anthropic.BetaMessageNewParams{
     	Model:     anthropic.ModelClaudeFable5_1,
     	MaxTokens: 4096,
     	OutputConfig: anthropic.BetaOutputConfigParam{
     		Effort: anthropic.BetaOutputConfigEffortHigh,
     	},
     	Messages: []anthropic.BetaMessageParam{
     		anthropic.NewBetaUserMessage(anthropic.NewBetaTextBlock("Plan a migration from SQLite to PostgreSQL in three short steps.")),
     		{OfAssistant: &anthropic.BetaAssistantMessageParam{
     			Content: []anthropic.BetaContentBlockParamUnion{anthropic.NewBetaTextBlock("1. Export the SQLite data. 2. Create the PostgreSQL schema. 3. Import the data and verify row counts.")},
     		}},
     		// Effort-only system message: the new level takes effect from the next user turn.
     		anthropic.NewBetaSystemMessage(anthropic.BetaSystemMessageOutputConfigParam{
     			Effort: anthropic.BetaSystemMessageOutputConfigEffortLow,
     		}),
     		anthropic.NewBetaUserMessage(anthropic.NewBetaTextBlock("Summarize the plan in one sentence.")),
     	},
     	Betas: []anthropic.AnthropicBeta{anthropic.AnthropicBetaMidConversationOutputConfig2026_07_01},
     })
     if err != nil {
     	log.Fatal(err)
     }

     for _, block := range response.Content {
     	if textBlock, ok := block.AsAny().(anthropic.BetaTextBlock); ok {
     		fmt.Println(textBlock.Text)
     	}
     }
     ```

     ```java Java
     import com.anthropic.models.beta.AnthropicBeta;
     import com.anthropic.models.beta.messages.BetaMessage;
     import com.anthropic.models.beta.messages.BetaOutputConfig;
     import com.anthropic.models.beta.messages.BetaSystemMessageOutputConfig;
     import com.anthropic.models.beta.messages.BetaSystemMessageParam;
     import com.anthropic.models.beta.messages.MessageCreateParams;
     import com.anthropic.models.messages.Model;

     void main() {
         AnthropicClient client = AnthropicOkHttpClient.fromEnv();

         MessageCreateParams params = MessageCreateParams.builder()
             .model(Model.CLAUDE_FABLE_5_1)
             .maxTokens(4096L)
             .addBeta(AnthropicBeta.MID_CONVERSATION_OUTPUT_CONFIG_2026_07_01)
             .outputConfig(BetaOutputConfig.builder()
                 .effort(BetaOutputConfig.Effort.HIGH)
                 .build())
             .addUserMessage("Plan a migration from SQLite to PostgreSQL in three short steps.")
             .addAssistantMessage("1. Export the SQLite data. 2. Create the PostgreSQL schema. 3. Import the data and verify row counts.")
             // Effort-only system message: the new level takes effect from the next user turn.
             .addMessage(BetaSystemMessageParam.builder()
                 .contentOfBlocks(List.of())
                 .outputConfig(BetaSystemMessageOutputConfig.builder()
                     .effort(BetaSystemMessageOutputConfig.Effort.LOW)
                     .build())
                 .build())
             .addUserMessage("Summarize the plan in one sentence.")
             .build();

         BetaMessage response = client.beta().messages().create(params);
         response.content().stream()
             .flatMap(block -> block.text().stream())
             .forEach(textBlock -> IO.println(textBlock.text()));
     }
     ```

     ```php PHP
     use Anthropic\Beta\AnthropicBeta;
     use Anthropic\Beta\Messages\BetaMessageParam;
     use Anthropic\Beta\Messages\BetaOutputConfig;
     use Anthropic\Beta\Messages\BetaSystemMessageOutputConfig;
     use Anthropic\Client;

     $client = new Client();

     $response = $client->beta->messages->create(
         model: 'claude-fable-5-1',
         maxTokens: 4096,
         outputConfig: BetaOutputConfig::with(effort: 'high'),
         messages: [
             BetaMessageParam::with(role: 'user', content: 'Plan a migration from SQLite to PostgreSQL in three short steps.'),
             BetaMessageParam::with(role: 'assistant', content: '1. Export the SQLite data. 2. Create the PostgreSQL schema. 3. Import the data and verify row counts.'),
             // Effort-only system message: the new level takes effect from the next user turn.
             BetaMessageParam::with(
                 role: 'system',
                 content: [],
                 outputConfig: BetaSystemMessageOutputConfig::with(effort: 'low'),
             ),
             BetaMessageParam::with(role: 'user', content: 'Summarize the plan in one sentence.'),
         ],
         betas: [AnthropicBeta::MID_CONVERSATION_OUTPUT_CONFIG_2026_07_01],
     );

     foreach ($response->content as $block) {
         if ($block->type === 'text') {
             echo $block->text, PHP_EOL;
         }
     }
     ```

     ```ruby Ruby
     client = Anthropic::Client.new

     response = client.beta.messages.create(
       model: Anthropic::Model::CLAUDE_FABLE_5_1,
       max_tokens: 4096,
       output_config: {effort: :high},
       messages: [
         {role: "user", content: "Plan a migration from SQLite to PostgreSQL in three short steps."},
         {role: "assistant", content: "1. Export the SQLite data. 2. Create the PostgreSQL schema. 3. Import the data and verify row counts."},
         # Effort-only system message: the new level takes effect from the next user turn.
         {role: "system", content: [], output_config: {effort: :low}},
         {role: "user", content: "Summarize the plan in one sentence."}
       ],
       betas: [Anthropic::AnthropicBeta::MID_CONVERSATION_OUTPUT_CONFIG_2026_07_01]
     )

     response.content.each do |block|
       puts block.text if block.type == :text
     end
     ```
   </CodeGroup>

   Placed between an `assistant` turn and the next `user` turn, as here, the message takes effect from that `user` turn. Placed directly after a `user` turn with new input, it sets the level for Claude’s reply to that turn. A `user` turn that holds only tool results doesn’t count as new input: the change waits for the next `user` turn with new input. The level then holds until another `role: "system"` message changes it. Only the named levels are accepted (`low`, `medium`, `high`, `xhigh`, `max`), and the `mid-conversation-output-config-2026-07-01` beta header is required. See [Per-message effort](https://platform.claude.com/docs/en/build-with-claude/effort#change-effort-mid-conversation-beta).

2. **Change instructions and tools with mid-conversation system messages:** To change instructions or tools partway through a session, append a [`role: "system"` message](https://platform.claude.com/docs/en/build-with-claude/mid-conversation-system-messages), with `tool_addition` and `tool_removal` blocks for tool changes. On the Claude API, Claude Platform on AWS, and Claude Models on Google Cloud (Anthropic managed), send the beta header `inline-tools-2026-09-15` for tool changes. A `tool_addition` block can name a tool declared in `tools` at session start or [carry the tool’s full definition](https://platform.claude.com/docs/en/build-with-claude/mid-conversation-system-messages#define-tools-in-a-message-beta), so a tool that is unknown at session start doesn’t need to be in `tools`. This preserves prompt cache hits on earlier turns and keeps the conversation history append-only. The `mid-conversation-tool-changes-2026-07-01` header works for changes that name a tool by reference, on the Claude API, Amazon Bedrock, Claude Platform on AWS, Claude Models on Google Cloud (Anthropic managed), and Claude Models on Google Cloud (Google managed). The same message replaces forced `tool_choice` when a specific tool must run on the current turn (see [Breaking changes](https://platform.claude.com/docs/en/models/fable-5-1/migration-guide#fable-5-1-breaking-changes)). For a reminder that applies to one turn only, send it as a separate text-only `role: "system"` message with `clear_at: "next_user_message"` ([turn-scoped system messages](https://platform.claude.com/docs/en/build-with-claude/mid-conversation-system-messages#turn-scoped-system-messages), beta header `mid-conversation-system-clear-at-2026-08-21`) and leave it in the history: it stops rendering after the next user message and costs no tokens once cleared. A message that carries `tool_addition` or `tool_removal` blocks can’t be turn-scoped.

3. **Use `fallbacks: "default"` for refusals:** Keep handling `stop_reason: "refusal"` and reading `stop_details.category` before response content. To re-run refused requests on another model automatically, set `fallbacks: "default"` (beta, `server-side-fallback-2026-07-01` header). `"default"` retries a declined request on the model Anthropic recommends for that category. The permitted fallback targets for Claude Fable 5.1 are Claude Opus 4.8 (`claude-opus-4-8`) and Claude Opus 5 (`claude-opus-5`). An explicit `fallbacks` list may name either. The fallback model doesn’t receive Claude Fable 5.1’s thinking blocks. The `fallbacks` parameter isn’t available on Amazon Bedrock, Claude Models on Google Cloud (Google managed), or Microsoft Foundry. On those platforms, use [client-side fallback](https://platform.claude.com/docs/en/build-with-claude/refusals-and-fallback#client-side-fallback) instead. If you build the retry yourself, [fallback credit](https://platform.claude.com/docs/en/build-with-claude/fallback-credit) applies on the same terms as Claude Fable 5. See [Refusals and fallback](https://platform.claude.com/docs/en/build-with-claude/refusals-and-fallback).

4. **Start at `high` effort and sweep:** The [effort parameter](https://platform.claude.com/docs/en/build-with-claude/effort) default is `high`, and all five levels are supported. Keep the Claude Fable 5 guidance: `high` for most work, and `medium` as a cost control worth testing. Claude Fable 5.1’s gains over Claude Fable 5 are largest at `xhigh` and `max`, but those levels also add thinking time and time-to-first-response, so step up to them for the most capability-sensitive tasks and where your evals show the gain. Run a fresh sweep on your own evals rather than carrying over a setting tuned for Claude Fable 5. See [Recommended effort levels for Claude Fable 5.1](https://platform.claude.com/docs/en/build-with-claude/effort#recommended-effort-levels-for-claude-fable-5-1).

5. **Trim context on the server, or compact in a shape that carries no stale thinking:** If your code truncates or summarizes older turns on the client, the simplest fix is to move that work to server-side [compaction](https://platform.claude.com/docs/en/build-with-claude/compaction) or [context editing](https://platform.claude.com/docs/en/build-with-claude/context-editing). Neither counts as an edit: the [prefix check](https://platform.claude.com/docs/en/models/fable-5-1/migration-guide#fable-5-1-preserved-thinking) compares the conversation as you sent it, so nothing they remove invalidates later thinking blocks. Compaction’s [`instructions` parameter](https://platform.claude.com/docs/en/build-with-claude/compaction-threshold#custom-summarization-instructions) also accepts your own summarization prompt. If you keep recent turns verbatim behind the summary, or summarize in the background while the conversation continues, use [on-demand compaction](https://platform.claude.com/docs/en/build-with-claude/compaction-on-demand) (beta header `compact-2026-09-04`) rather than a client-written summary. The API writes a signed summary block that you put in place of the messages it summarizes. The thinking blocks in the turns you keep can stay valid, under the conditions in [Compaction and preserved thinking](https://platform.claude.com/docs/en/build-with-claude/compaction-thinking-blocks#conditions-for-kept-thinking-to-stay-valid). If you keep compaction on the client, pick one of three shapes:

   * **Simple compaction (recommended):** replace the whole history with one summary message plus the new user turn and replay nothing else. No thinking blocks are carried over, so nothing fails. Claude models are trained on long-horizon tasks with this scheme, and it performs comparably to more elaborate ones for most workloads.
   * **Keep-tail compaction:** if you keep the most recent turns verbatim behind a summary, strip the `thinking` and `redacted_thinking` blocks from those turns (text and tool calls can stay), or set `prefix_mismatch_behavior: "drop_block"`. Their thinking was produced against the full history and fails behind the summary otherwise.
   * **Background compaction:** if you build the summary off the critical path and swap it in later, every turn produced in the meantime carries thinking that predates the swap. Send `"drop_block"` on every request that still carries thinking blocks produced before the swap (or strip those blocks yourself; `input_transformations` on the first response after the swap lists exactly which ones), or compact synchronously.

   Don’t snip individual turns out of the middle of the transcript: that invalidates every later thinking block and no client-side shape avoids it. Use a [mid-conversation system message](https://platform.claude.com/docs/en/build-with-claude/mid-conversation-system-messages) for the instruction change you were making, or server-side [context editing](https://platform.claude.com/docs/en/build-with-claude/context-editing) for selective removal. See [Passing compaction blocks back](https://platform.claude.com/docs/en/build-with-claude/compaction-threshold#passing-compaction-blocks-back).

### Migration checklist

* Update the model name from `claude-fable-5` to `claude-fable-5-1` (or `claude-mythos-5` to `claude-mythos-5-1`).
* Replace forced `tool_choice` (`{type: "any"}` or `{type: "tool", ...}`): a request that sets it gets a 400 error. Use `{type: "auto"}` with an explicit instruction and `strict: true` tools, or use JSON outputs. When your application requires the call, put the instruction in the `user` turn or in a mid-conversation `role: "system"` message.
* If you use the [advisor tool](https://platform.claude.com/docs/en/agents-and-tools/tool-use/advisor-tool) (beta), update the advisor `model` as well. An advisor less capable than Claude Fable 5.1, such as `claude-fable-5` or `claude-opus-5-5`, returns a 400 error.
* Keep passing `thinking` blocks back unchanged on every turn, including empty ones. Claude Fable 5.1 and Claude Mythos 5.1 read blocks from Claude Opus 5, Claude Fable 5, Claude Mythos 5, and earlier models. Moving a conversation from Claude Fable 5.1 to any model other than Claude Mythos 5.1 drops its blocks.
* If your code builds the `messages` array itself, check whether it [edits earlier turns](https://platform.claude.com/docs/en/models/fable-5-1/migration-guide#fable-5-1-preserved-thinking): run a session with the `thinking-binding-controls-2026-08-01` beta header and `prefix_mismatch_behavior: "drop_block"`, log `input_transformations`, and fix every `prefix_binding_mismatch`. `model_binding_mismatch` entries after a model switch are expected.
* Keep conversation history append-only. Freeze `system` and `tools` at session start and move mid-session changes to `role: "system"` messages and `tool_addition` / `tool_removal` blocks. Send per-turn reminders as turn-scoped system messages you never remove. Trim context server-side or strip thinking blocks from any turns you carry across a client-side summary. Reference cross-turn files by `file_id`.
* Set `prefix_mismatch_behavior` on every production request. `"error"` fails a request that sends back an invalid thinking block. `"drop_block"` drops the invalid blocks and lets the request succeed. Monitor the 400 errors or the `input_transformations` entries.
* Review agent loops for one-tool-call-per-turn behavior and add the batching instruction.
* If your interface renders progress text between tool calls, set `thinking.display` to `"updates"` (beta) or `"summarized"` and prompt for updates.
* If you change effort between requests, move the change to a [per-message effort](https://platform.claude.com/docs/en/build-with-claude/effort#change-effort-mid-conversation-beta) `role: "system"` message (beta) to keep cache hits.
* Handle `stop_reason: "refusal"` and read `stop_details.category`. Consider `fallbacks: "default"` (beta).
* Re-evaluate `effort` with a fresh sweep, starting at `high`, and re-baseline cost and latency on your own workloads. The tokenizer is unchanged. Prompt cache reads cost a quarter of the Claude Fable 5 rate.
* If you have a [Priority Tier commitment](https://platform.claude.com/docs/en/api/service-tiers#existing-priority-tier-commitments) for your current model, it doesn’t cover Claude Fable 5.1, which isn’t supported on Priority Tier.

## Migrating to Claude Fable 5.1 from Claude Opus 5

Claude Fable 5.1 uses the same [Messages API](https://platform.claude.com/docs/en/build-with-claude/working-with-messages) and [tool use](https://platform.claude.com/docs/en/agents-and-tools/tool-use/overview) patterns as Claude Opus 5. It keeps the [1M token context window](https://platform.claude.com/docs/en/build-with-claude/context-windows) by default, [128k max output tokens](https://platform.claude.com/docs/en/models/overview), the 512-token prompt caching minimum, and [mid-conversation system message](https://platform.claude.com/docs/en/build-with-claude/mid-conversation-system-messages) support. The prefill restriction, the sampling-parameter restriction, and the `"omitted"` default for `thinking.display` also carry over. Apply everything in [Migrating to Claude Fable 5.1 from Claude Fable 5](https://platform.claude.com/docs/en/models/fable-5-1/migration-guide#migrating-from-claude-fable-5-to-claude-fable-5-1), plus the following.

### Update your model name

```python
model = "claude-opus-5"  # Before
model = "claude-fable-5-1"  # After

# Or, for Claude Mythos 5.1, which offers the same capabilities to verified organizations:
model = "claude-mythos-5-1"  # After
```

### What changed

1. **Thinking can’t be disabled:** Claude Opus 5 accepts `thinking: {type: "disabled"}` at an [effort](https://platform.claude.com/docs/en/build-with-claude/effort) level of `high` or lower. On `claude-fable-5-1` and `claude-mythos-5-1`, [adaptive thinking](https://platform.claude.com/docs/en/build-with-claude/thinking) is always on, and `thinking: {type: "disabled"}` returns a 400 error at any effort level. Remove the field, control token spend with lower effort levels, and revisit `max_tokens` for workloads that ran with thinking disabled. Responses from those workloads can start with `thinking` blocks, so select content blocks by `type` instead of by position.

2. **Forced tool choice is not supported:** Claude Opus 5 accepts `tool_choice` `any` and `tool`. `claude-fable-5-1` and `claude-mythos-5-1` return a 400 error. See [Breaking changes](https://platform.claude.com/docs/en/models/fable-5-1/migration-guide#fable-5-1-breaking-changes).

3. **Preserved thinking across models:** Claude Fable 5.1 and Claude Mythos 5.1 read Claude Opus 5’s thinking blocks: conversations moving from `claude-opus-5` to `claude-fable-5-1` or `claude-mythos-5-1` keep their reasoning. Claude Opus 5 can’t read blocks from either model. See [Breaking changes](https://platform.claude.com/docs/en/models/fable-5-1/migration-guide#fable-5-1-breaking-changes).

4. **Editing earlier turns invalidates thinking blocks:** Claude Opus 5 doesn’t run the prefix check. On `claude-fable-5-1` and `claude-mythos-5-1`, editing earlier messages, rebuilding `system` or `tools`, or compacting on the client between requests invalidates every later thinking block. Before you switch traffic, run the [three-step check](https://platform.claude.com/docs/en/models/fable-5-1/migration-guide#fable-5-1-check-integration) from the Claude Fable 5 section.

5. **Text between tool calls is returned in thinking blocks:** On Claude Opus 5, text the model writes between tool calls comes back as `text` blocks. On `claude-fable-5-1`, as on Claude Fable 5, that narration comes back as progress-update `thinking` blocks, one before each tool call. Under the default `thinking.display` of `"omitted"`, they carry no readable text. If your interface renders that narration, set `thinking.display` to `"updates"` (beta) to receive progress updates as text while reasoning stays hidden, or to `"summarized"` to receive both. Then render the non-empty `thinking` blocks between `tool_use` blocks. See [Progress updates between tool calls](https://platform.claude.com/docs/en/build-with-claude/thinking#progress-updates).

6. **Safety classifiers and fallback routing:** Claude Fable 5.1 runs safety classifiers covering the same `stop_details` categories as Claude Fable 5, a broader set than Claude Opus 5’s classifiers. Expect additional `stop_details.category` values, such as `"bio"`; see the [refusal category table](https://platform.claude.com/docs/en/build-with-claude/refusals-and-fallback#refusal-response) for the full set. For `fallbacks` configuration and permitted targets, see [Use `fallbacks: "default"` for refusals](https://platform.claude.com/docs/en/models/fable-5-1/migration-guide#fable-5-1-recommended-changes).

7. **Pricing:** $10 USD per million input tokens and $50 USD per million output tokens, compared with $5 USD and $25 USD for Claude Opus 5. Prompt cache reads are $0.25 USD per million tokens, half the Claude Opus 5 rate. See [Claude pricing](https://platform.claude.com/docs/en/about-claude/pricing).

8. **Data retention:** Claude Fable 5.1 and Claude Mythos 5.1 require 30-day data retention, aren’t available under zero data retention (ZDR) arrangements unless expressly authorized by Anthropic, and are designated Covered Models. Claude Opus 5 is available under ZDR. See [Model-specific data retention requirements](https://platform.claude.com/docs/en/manage-claude/api-and-data-retention#model-specific-data-retention-requirements).

### Migration checklist

* If your organization has a zero data retention (ZDR) arrangement, confirm eligibility first: these models aren’t available under ZDR unless expressly authorized by Anthropic. See [Model-specific data retention requirements](https://platform.claude.com/docs/en/manage-claude/api-and-data-retention#model-specific-data-retention-requirements).
* Update the model name from `claude-opus-5` to `claude-fable-5-1` (or `claude-mythos-5-1`).
* Remove any `thinking: {type: "disabled"}` configuration: it returns a 400 error on `claude-fable-5-1`. Control token spend with lower [effort](https://platform.claude.com/docs/en/build-with-claude/effort) levels, and revisit `max_tokens`.
* If you removed `thinking: {type: "disabled"}`, update response parsing that reads content by position, such as `content[0].text`: a response can start with `thinking` blocks, so select content blocks by `type` instead.
* Replace forced `tool_choice` (`any` or `tool`) with `auto` plus an explicit instruction (`user` turn or mid-conversation system message) and `strict: true` tools, or with JSON outputs.
* If your interface renders text between tool calls, set `display: "updates"` (beta) or `"summarized"` and render the non-empty `thinking` blocks.
* Apply the advisor, preserved-thinking, append-only, behavior, effort, and fallback items from the [Claude Fable 5 checklist](https://platform.claude.com/docs/en/models/fable-5-1/migration-guide#migration-checklist-fable-5-1-from-fable-5).
* Re-baseline cost on your own workloads. The tokenizer is unchanged. Per-token pricing differs.

## Migrating to Claude Fable 5.1 from Claude Opus 4.8 or earlier

Work through the following checklist. On Claude Opus 4.7 or earlier, start with the matching [Claude Opus 5.5 migration guide](https://platform.claude.com/docs/en/models/opus-5-5/migration-guide) section.

### Update your model name

```python
model = "claude-opus-4-8"  # Before
model = "claude-fable-5-1"  # After

# Or, for Claude Mythos 5.1, which offers the same capabilities to verified organizations:
model = "claude-mythos-5-1"  # After
```

### Migration checklist

* If your organization has a zero data retention (ZDR) arrangement, confirm eligibility first: these models aren’t available under ZDR unless expressly authorized by Anthropic. Claude Opus 4.8 is available under ZDR.
* Update the model name from `claude-opus-4-8` to `claude-fable-5-1` (or `claude-mythos-5-1`).
* Remove any `thinking: {type: "disabled"}` configuration and revisit `max_tokens`. Requests without a `thinking` field run with adaptive thinking.
* Update response parsing that reads content by position, such as `content[0].text`: a response can start with `thinking` blocks, so select content blocks by `type` instead.
* Replace forced `tool_choice` (`any` or `tool`) with `auto` plus an explicit instruction (`user` turn or mid-conversation system message) and `strict: true` tools, or with JSON outputs.
* Pass `thinking` blocks back unchanged and treat their text as display-only. Claude Fable 5.1 and Claude Mythos 5.1 read Claude Opus 4.8’s thinking blocks: a conversation that moves onto `claude-fable-5-1` or `claude-mythos-5-1` keeps its earlier reasoning. Claude Opus 4.8 can’t read their blocks.
* If your code builds the `messages` array itself, check whether it [edits earlier turns](https://platform.claude.com/docs/en/models/fable-5-1/migration-guide#fable-5-1-preserved-thinking). Integrations written for Claude Opus 4.8 and earlier often truncate old turns, strip or rebuild earlier messages, or refresh the `system` prompt each request, and Claude Opus 4.8 returns no error for any of them. On `claude-fable-5-1` and `claude-mythos-5-1`, each of those invalidates later thinking blocks.
* Handle `stop_reason: "refusal"`, read `stop_details.category`, and consider `fallbacks: "default"` (beta).
* Apply the advisor, Priority Tier, preserved-thinking, append-only, behavior, per-message effort, and progress-update items from the [Claude Fable 5 checklist](https://platform.claude.com/docs/en/models/fable-5-1/migration-guide#migration-checklist-fable-5-1-from-fable-5).
* Re-evaluate `effort` (start at `high`), review prompts near the 512-token [caching minimum](https://platform.claude.com/docs/en/build-with-claude/prompt-caching#cache-limitations) (1,024 tokens on Claude Opus 4.8), and re-baseline cost and latency. Per-token pricing differs, and thinking tokens are billed as output tokens, so workloads that ran without thinking on Claude Opus 4.8 can produce more output tokens per request.

## Migrating to Claude Mythos 5.1 from Claude Mythos 5

[Claude Mythos 5.1](https://platform.claude.com/docs/en/models/mythos-5-1/overview) is the counterpart to Claude Fable 5.1 for organizations verified through Anthropic’s verification programs, such as the [Cyber Verification Program](https://support.claude.com/en/articles/14604842). Confirm that your organization has access to Claude Mythos 5.1 before you switch model IDs.

Everything in [Migrating to Claude Fable 5.1 from Claude Fable 5](https://platform.claude.com/docs/en/models/fable-5-1/migration-guide#migrating-from-claude-fable-5-to-claude-fable-5-1) applies, with `claude-mythos-5` and `claude-mythos-5-1` in place of the Claude Fable model IDs. Claude Mythos 5.1 reads Claude Mythos 5’s thinking blocks; Claude Mythos 5 can’t read Claude Mythos 5.1’s. On Claude Mythos 5.1, a request that sends back an invalid thinking block and leaves `prefix_mismatch_behavior` unset gets a 400 error (see [When `prefix_mismatch_behavior` is unset](https://platform.claude.com/docs/en/build-with-claude/preserved-thinking#enforcement)).

### Update your model name

```python
model = "claude-mythos-5"  # Before
model = "claude-mythos-5-1"  # After
```

### Migration checklist

* Work through the [Claude Fable 5 checklist](https://platform.claude.com/docs/en/models/fable-5-1/migration-guide#migration-checklist-fable-5-1-from-fable-5) with the Claude Mythos model IDs. Skip its Priority Tier item: Claude Mythos 5 isn’t supported on Priority Tier.
* Run its check for [edits to earlier turns](https://platform.claude.com/docs/en/models/fable-5-1/migration-guide#fable-5-1-preserved-thinking) before you switch: Claude Mythos 5 accepts those edits, but they invalidate Claude Mythos 5.1’s thinking blocks.